Abstract is missing.
- LIVELINET: A Multimodal Deep Recurrent Neural Network to Predict Liveliness in Educational VideosArjun Sharma, Arijit Biswas, Ankit Gandhi, Sonal Patil, Om Deshmukh. [doi]
- Measuring Gameplay Affordances of User-Generated Content in an Educational GameAndrew Hicks, Zhongxiu Liu, Tiffany Barnes. [doi]
- How to Model Implicit Knowledge? Similarity Learning Methods to Assess Perceptions of Visual RepresentationsMartina A. Rau, Blake Mason, Robert D. Nowak. [doi]
- Calibrated Self-AssessmentIgor Labutov, Christoph Studer. [doi]
- How Deep is Knowledge Tracing?Mohammad Khajah, Robert V. Lindsey, Michael Mozer. [doi]
- Data-Driven Education: Some opportunities and ChallengesRakesh Agrawal. 2 [doi]
- WISE Ways to Strengthen Inquiry Science LearningMarcia Linn. 3 [doi]
- Enabling people to harness and control EDM for lifelong, life-wide learningJudy Kay. 4 [doi]
- Toward Data-Driven Design of Educational Courses: A Feasibility StudyRakesh Agrawal, Behzad Golshan, Evangelos E. Papalexakis. 6 [doi]
- Next-Term Student Performance Prediction: A Recommender Systems ApproachMack Sweeney, Jaime Lester, Huzefa Rangwala, Aditya Johri. 7 [doi]
- Exploring the Effect of Student Confusion in Massive Open Online CoursesDiyi Yang, Robert Kraut, Carolyn Penstein Rosé. 8 [doi]
- Enabling people to harness and control EDM for lifelong, life-wide learningJudy Kay. 10-20 [doi]
- {ENTER}ing the Time Series {SPACE}: Uncovering the Writing Process through Keystroke AnalysesLaura K. Allen, Matthew E. Jacovina, Mihai Dascalu, Rod D. Roscoe, Kevin Kent, Aaron D. Likens, Danielle S. McNamara. 22-29 [doi]
- Automatic Gaze-Based Detection of Mind Wandering during Film ViewingCaitlin Mills, Robert Bixler, Xinyi Wang, Sidney K. D'Mello. 30-37 [doi]
- Riding an emotional roller-coaster: A multimodal study of young child's math problem solving activitiesLujie Chen, Xin Li, Zhuyun Xia, Zhanmei Song, Louis-Philippe Morency, Artur Dubrawski. 38-45 [doi]
- Joint Discovery of Skill Prerequisite Graphs and Student ModelsYetian Chen, José P. González-Brenes, Jin Tian. 46-53 [doi]
- Gauging MOOC Learners' Adherence to the Designed Learning PathDan Davis, Guanliang Chen, Claudia Hauff, Geert-Jan Houben. 54-61 [doi]
- Dynamics of Peer Grading: An Empirical StudyLuca de Alfaro, Michael Shavlovsky. 62-69 [doi]
- Sequence Matters, But How Exactly? A Method for Evaluating Activity Sequences from DataShayan Doroudi, Kenneth Holstein, Vincent Aleven, Emma Brunskill. 70-77 [doi]
- Measuring Gameplay Affordances of User-Generated Content in an Educational GameAndrew Hicks, Zhongxiu Liu, Michael Eagle, Tiffany Barnes. 78-85 [doi]
- The Eyes Have It: Gaze-based Detection of Mind Wandering during Learning with an Intelligent Tutoring SystemStephen Hutt, Caitlin Mills, Shelby White, Patrick J. Donnelly, Sidney K. D'Mello. 86-93 [doi]
- How Deep is Knowledge Tracing?Mohammad Khajah, Robert V. Lindsey, Michael Mozer. 94-101 [doi]
- Temporally Coherent Clustering of Student DataSeverin Klingler, Tanja Käser, Barbara Solenthaler, Markus H. Gross. 102-109 [doi]
- Web as a textbook: Curating Targeted Learning Paths through the Heterogeneous Learning Resources on the WebIgor Labutov, Hod Lipson. 110-118 [doi]
- Calibrated Self-AssessmentIgor Labutov, Christoph Studer. 119-126 [doi]
- MOOC Learner Behaviors by Country and Culture; an Exploratory AnalysisZhongxiu Liu, Rebecca Brown, Collin Lynch, Tiffany Barnes, Ryan S. Baker, Yoav Bergner, Danielle S. McNamara. 127-134 [doi]
- Effect of student ability and question difficulty on durationYijun Ma, Lalitha Agnihotri, Ryan S. Baker, Shirin Mojarad. 135-142 [doi]
- Modeling the Influence of Format and Depth during Effortful Retrieval PracticeJaclyn K. Maass, Philip I. Pavlik Jr.. 143-150 [doi]
- The Apprentice Learner architecture: Closing the loop between learning theory and educational dataChristopher J. MacLellan, Erik Harpstead, Rony Patel, Kenneth R. Koedinger. 151-158 [doi]
- Mining behaviors of students in autograding submission system logsJessica McBroom, Bryn Jeffries, Irena Koprinska, Kalina Yacef. 159-166 [doi]
- Modelling the way: Using action sequence archetypes to differentiate learning pathways from learning outcomesKelvin H. R. Ng, Kevin Hartman, Kai Liu, Andy W. H. Khong. 167-174 [doi]
- A Coupled User Clustering Algorithm for Web-based Learning SystemsKe Niu, Zhendong Niu, Xiangyu Zhao, Can Wang, Kai Kang, Min Ye. 175-182 [doi]
- Execution Traces as a Powerful Data Representation for Intelligent Tutoring Systems for ProgrammingBenjamin Paaßen, Joris Jensen, Barbara Hammer. 183-190 [doi]
- Generating Data-driven Hints for Open-ended ProgrammingThomas W. Price, Yihuan Dong, Tiffany Barnes. 191-198 [doi]
- How to Model Implicit Knowledge? Similarity Learning Methods to Assess Perceptions of Visual RepresentationsMartina A. Rau, Blake Mason, Robert D. Nowak. 199-206 [doi]
- Student Usage Predicts Treatment Effect Heterogeneity in the Cognitive Tutor Algebra I ProgramAdam Sales, Asa Wilks, John Pane. 207-214 [doi]
- LIVELINET: A Multimodal Deep Recurrent Neural Network to Predict Liveliness in Educational VideosArjun Sharma, Arijit Biswas, Ankit Gandhi, Sonal Patil, Om Deshmukh. 215-222 [doi]
- Semantic Features of Math Problems: Relationships to Student Learning and EngagementStefan Slater, Jaclyn Ocumpaugh, Ryan S. Baker, Peter Scupelli, Paul Salvador Inventado, Neil T. Heffernan. 223-230 [doi]
- An Ensemble Method to Predict Student Performance in an Online Math Learning EnvironmentMartin Stapel, Zhilin Zheng, Niels Pinkwart. 231-238 [doi]
- Predicting Post-Test Performance from Student Behavior: A High School MOOC Case StudySabina Tomkins, Arti Ramesh, Lise Getoor. 239-246 [doi]
- The Affective Impact of Tutor Questions: Predicting Frustration and EngagementAlexandria Katarina Vail, Joseph B. Wiggins, Joseph F. Grafsgaard, Kristy Elizabeth Boyer, Eric N. Wiebe, James C. Lester. 247-254 [doi]
- Unnatural Feature Engineering: Evolving Augmented Graph Grammars for Argument DiagramsLinting Xue, Collin Lynch, Min Chi. 255-262 [doi]
- Investigating Swarm Intelligence for Performance PredictionMohammad Majid al-Rifaie, Matthew Yee-King, Mark d'Inverno. 264-269 [doi]
- Predicting Student Progress from Peer-Assessment DataMichael Mogessie Ashenafi, Marco Ronchetti, Giuseppe Riccardi. 270-275 [doi]
- Topic-wise Classification of MOOC Discussions: A Visual Analytics ApproachThushari Atapattu, Katrina Falkner, Hamid Tarmazdi. 276-281 [doi]
- Document Segmentation for Labeling with Academic Learning ObjectivesDivyanshu Bhartiya, Danish Contractor, Sovan Biswas, Bikram Sengupta, Mukesh K. Mohania. 282-287 [doi]
- Semi-Automatic Detection of Teacher Questions from Human-Transcripts of Audio in Live ClassroomsNathaniel Blanchard, Patrick J. Donnelly, Andrew Olney, Borhan Samei, Sean Kelly, Xiaoyi Sun, Brooke Ward, Martin Nystrand, Sidney K. D'Mello. 288-291 [doi]
- Modeling Interactions Across Skills: A Method to Construct and Compare Models Predicting the Existence of Skill RelationshipsAnthony F. Botelho, Seth Adjei, Neil T. Heffernan. 292-297 [doi]
- Robust Predictive Models on MOOCs : Transferring Knowledge across CoursesSebastien Boyer, Kalyan Veeramachaneni. 298-305 [doi]
- A Comparative Analysis of Techniques for Predicting Student PerformanceHana Bydzovská. 306-311 [doi]
- Course Enrollment Recommender SystemHana Bydzovská. 312-317 [doi]
- Data-driven Automated Induction of Prerequisite Structure GraphsDevendra Singh Chaplot, Yiming Yang, Jaime G. Carbonell, Kenneth R. Koedinger. 318-323 [doi]
- Exploring Learning Management System Interaction Data: Combining Data-driven and Theory-driven ApproachesHongkyu Choi, Ji-eun Lee, Won-Joon Hong, Kyumin Lee, Mimi Recker, Andy Walker. 324-329 [doi]
- A Comparison of Automatic Teaching Strategies for Heterogeneous Student PopulationsBenjamin Clement, Pierre-Yves Oudeyer, Manuel Lopes. 330-335 [doi]
- Automatic Assessment of Constructed Response Data in a Chemistry TutorScott A. Crossley, Kris Kyle, Jodi L. Davenport, Danielle S. McNamara. 336-340 [doi]
- Choosing versus Receiving Feedback: The Impact of Feedback Valence on Learning in an Assessment GameMaria Cutumisu, Daniel L. Schwartz. 341-346 [doi]
- Course Content Analysis: An Initiative Step toward Learning Object Recommendation Systems for MOOC LearnersYiling Dai, Yasuhito Asano, Masatoshi Yoshikawa. 347-352 [doi]
- Student Emotion, Co-occurrence, and Dropout in a MOOC ContextJohn Dillon, Nigel Bosch, Malolan Chetlur, Nirandika Wanigasekara, G. Alex Ambrose, Bikram Sengupta, Sidney K. D'Mello. 353-357 [doi]
- Semi-Markov model for simulating MOOC studentsLouis Faucon, Lukasz Kidzinski, Pierre Dillenbourg. 358-363 [doi]
- Investigating Gender Difference on Homework in Middle School MathematicsMingyu Feng, Jeremy Roschelle, Craig Mason, Ruchi Bhanot. 364-369 [doi]
- Investigating Difficult Topics in a Data Structures Course Using Item Response Theory and Logged Data AnalysisEric Fouh, Mohammed F. Farghally, Sally Hamouda, Kyu Han Koh, Clifford A. Shaffer. 370-375 [doi]
- Acting the Same Differently: A Cross-Course Comparison of User Behavior in MOOCsBen U. Gelman, Matt Revelle, Carlotta Domeniconi, Kalyan Veeramachaneni, Aditya Johri. 376-381 [doi]
- Collaborative Problem Solving Skills versus Collaboration Outcomes: Findings from Statistical Analysis and Data MiningJiangang Hao, Lei Liu, Alina Von Davier, Patrick Kyllonen, Christopher Kitchen. 382-387 [doi]
- Hint Availability Slows Completion Times in Summer WorkPaul Salvador Inventado, Peter Scupelli, Eric Van Inwegen, Korinn Ostrow, Neil Heffernan III, Jaclyn Ocumpaugh, Ryan S. Baker, Stefan Slater, Mia Almeda. 388-393 [doi]
- On Competition for Undergraduate Co-op Placements: A Graph Mining ApproachYuheng Helen Jiang, Lukasz Golab. 394-399 [doi]
- Expediting Support for Social Learning with Behavior ModelingYohan Jo, Gaurav Tomar, Oliver Ferschke, Carolyn Penstein Rosé, Dragan Gasevic. 400-405 [doi]
- On generalizability of MOOC modelsLukasz Kidzinski, Kshitij Sharma, Mina Shirvani Boroujeni, Pierre Dillenbourg. 406-411 [doi]
- Closing the Loop with Quantitative Cognitive Task AnalysisKenneth R. Koedinger, Elizabeth A. McLaughlin. 412-417 [doi]
- Does a Peer Recommender Foster Students' Engagement in MOOCs?Hugues Labarthe, François Bouchet, Rémi Bachelet, Kalina Yacef. 418-423 [doi]
- A Contextual Bandits Framework for Personalized Learning Action SelectionAndrew S. Lan, Richard G. Baraniuk. 424-429 [doi]
- How Good Is Popularity? Summary Grading in CrowdsourcingHaiying Li, Zhiqiang Cai, Arthur C. Graesser. 430-435 [doi]
- Beyond Log Files: Using Multi-Modal Data Streams Towards Data-Driven KC Model ImprovementRan Liu, Jodi L. Davenport, John C. Stamper. 436-441 [doi]
- Seeking Programming-related Information from Large Scaled Discussion Forums, Help or Harm?Yihan Lu, Sharon I-Han Hsiao. 442-447 [doi]
- Classifying behavior to elucidate elegant problem solving in an educational gameLaura Malkiewich, Ryan S. Baker, Valerie Shute, Shiming Kai, Luc Paquette. 448-453 [doi]
- Predicting Dialogue Acts for Intelligent Virtual Agents with Multimodal Student Interaction DataWookhee Min, Joseph B. Wiggins, Lydia Pezzullo, Alexandria Katarina Vail, Kristy Elizabeth Boyer, Bradford W. Mott, Megan Frankosky, Eric N. Wiebe, James C. Lester. 454-459 [doi]
- Exploring the Impact of Data-driven Tutoring Methods on Students' Demonstrative Knowledge in Logic Problem SolvingBehrooz Mostafavi, Tiffany Barnes. 460-465 [doi]
- Properties and Applications of Wrong Answers in Online Educational SystemsRadek Pelánek, Jirí Rihák. 466-471 [doi]
- Using Inverse Planning for Personalized FeedbackAnna N. Rafferty, Rachel Jansen, Thomas L. Griffiths. 472-477 [doi]
- Pattern mining uncovers social prompts of conceptual learning with physical and virtual representationsMartina A. Rau. 478-483 [doi]
- Predicting Performance on MOOC Assessments using Multi-Regression ModelsZhiyun Ren, Huzefa Rangwala, Aditya Johri. 484-489 [doi]
- Validating Game-based Measures of Implicit Science LearningElizabeth Rowe, Jodi Asbell-Clarke, Michael Eagle, Andrew Hicks, Tiffany Barnes, Rebecca Brown, Teon Edwards. 490-495 [doi]
- Assessing Student-Generated Design Justifications in Virtual Engineering InternshipsVasile Rus, Dipesh Gautam, Zach Swiecki, David W. Shaffer, Art Graesser. 496-501 [doi]
- Tensor Factorization for Student Modeling and Performance Prediction in Unstructured DomainShaghayegh Sahebi, Yu-Ru Lin, Peter Brusilovsky. 502-506 [doi]
- Aim Low: Correlation-based Feature Selection for Model-based Reinforcement LearningShitian Shen, Min Chi. 507-512 [doi]
- Personalization of Learning Paths in Online Communities of CreatorsMingxuan Sun, Seungwon Yang. 513-516 [doi]
- Modeling Visitor Behavior in a Game-Based Engineering Museum Exhibit with Hidden Markov ModelsMichael Tissenbaum, Matthew Berland, Vishesh Kumar. 517-522 [doi]
- Learning Curves for Problems with Multiple Knowledge ComponentsBrett van de Sande. 523-526 [doi]
- A Nonlinear State Space Model for Identifying At-Risk Students in Open Online CoursesFeng Wang, Li Chen. 527-532 [doi]
- Transactivity as a Predictor of Future Collaborative Knowledge Integration in Team-Based Learning in Online CoursesMiaomiao Wen, Keith Maki, Xu Wang, Steven Dow, James D. Herbsleb, Carolyn Penstein Rosé. 533-538 [doi]
- Back to the basics: Bayesian extensions of IRT outperform neural networks for proficiency estimationKevin H. Wilson, Yan Karklin, Bojian Han, Chaitanya Ekanadham. 539-544 [doi]
- Going Deeper with Deep Knowledge TracingXiaolu Xiong, Siyuan Zhao, Eric Van Inwegen, Joseph Beck. 545-550 [doi]
- Boosted Decision Tree for Q-matrix RefinementPeng Xu, Michel Desmarais. 551-555 [doi]
- Individualizing Bayesian Knowledge Tracing. Are Skill Parameters More Important Than Student Parameters?Michael Yudelson. 556-561 [doi]
- Deep Learning + Student Modeling + Clustering: a Recipe for Effective Automatic Short Answer GradingYuan Zhang, Rajat Shah, Min Chi. 562-567 [doi]
- Redefining "What" in Analyses of Who Does What in MOOCsAlok Baikadi, Carrie Demmans Epp, Yanjin Long, Christian Schunn. 569-570 [doi]
- Text Classification of Student Self-Explanations in College Physics QuestionsSameer Bhatnagar, Michel Desmarais, Nathaniel Lasry, Elizabeth S. Charles. 571-572 [doi]
- Automated Feedback on the Quality of Collaborative Processes: An Experience ReportMarcela Borge, Carolyn Penstein Rosé. 573-574 [doi]
- Mining Sequences of Gameplay for Embedded Assessment in Collaborative LearningPhilip Sheridan Buffum, Megan Frankosky, Kristy Elizabeth Boyer, Eric N. Wiebe, Bradford W. Mott, James C. Lester. 575-576 [doi]
- Can Word Probabilities from LDA be Simply Added up to Represent Documents?Zhiqiang Cai, Haiying Li, Xiangen Hu, Art Graesser. 577-578 [doi]
- Examining the necessity of problem diagrams using MOOC AB experimentsZhongzhou Chen, Neset Demirci, David E. Pritchard. 579-580 [doi]
- Identifying relevant user behavior and predicting learning and persistence in an ITS-based afterschool programScotty D. Craig, Xudong Huang, Jun Xie, Ying Fang, Xiangen Hu. 581-582 [doi]
- Extracting Measures of Active Learning and Student Self-Regulated Learning Strategies from MOOC DataNicholas Diana, Michael Eagle, John C. Stamper, Kenneth R. Koedinger. 583-584 [doi]
- Exploring Social Influence on the Usage of Resources in an Online Learning CommunityOgheneovo Dibie, Tamara Sumner, Keith E. Maull, David Quigley. 585-586 [doi]
- Time Series Cross Section method for monitoring students' page views of course materials and improving classroom teachingKonomu Dobashi. 587-588 [doi]
- Predicting STEM Achievement with Learning Management System Data: Prediction Modeling and a Test of an Early Warning SystemMichelle Dominguez, Matthew L. Bernacki, Phillip Merlin Uesbeck. 589-590 [doi]
- Comparison of Selection Criteria for Multi-Feature Hierarchical Activity Mining in Open Ended Learning EnvironmentsYi Dong, John S. Kinnebrew, Gautam Biswas. 591-592 [doi]
- A Data-Driven Framework of Modeling Skill Combinations for Deeper Knowledge TracingYun Huang, Julio Guerra, Peter Brusilovsky. 593-594 [doi]
- Generating Semantic Concept Map for MOOCsZhuoxuan Jiang, Peng Li, Yan Zhang, Xiaoming Li. 595-596 [doi]
- How to Judge Learning on Online Learning: Minimum Learning Judgment SystemJaechoon Jo, HeuiSeok Lim. 597-598 [doi]
- Guiding Students Towards Frequent High-Utility Paths in an Ill-Defined DomainIgor Jugo, Bozidar Kovacic, Vanja Slavuj. 599-600 [doi]
- Portrait of an Indexer - Computing Pointers Into Instructional VideosAndrew Lamb, Jose Hernandez, Jeffrey D. Ullman, Andreas Paepcke. 601-602 [doi]
- Hierarchical Cluster Analysis Heatmaps and Pattern Analysis: An Approach for Visualizing Learning Management System Interaction DataJi-eun Lee, Mimi Recker, Alex Bowers, Min Yuan. 603-604 [doi]
- Understanding Engagement in MOOCsQiujie Li, Rachel Baker. 605-606 [doi]
- How quickly can wheel spinning be detected?Noboru Matsuda, Sanjay Chandrasekaran, John C. Stamper. 607-608 [doi]
- Exploring and Following Students' Strategies When Completing Their Weekly TasksJessica McBroom, Bryn Jeffries, Irena Koprinska, Kalina Yacef. 609-610 [doi]
- Identifying Student Behaviors Early in the Term for Improving Online Course PerformanceMakoto Mori, Philip Chan. 611-612 [doi]
- Time Series Analysis of VLE Activity DataEwa Mlynarska, Pádraig Cunningham, Derek Greene. 613-614 [doi]
- Massively Scalable EDM with SparkTristan Nixon. 615 [doi]
- Study on Automatic Scoring of Descriptive Type Tests using Text Similarity CalculationsIzuru Nogaito, Keiji Yasuda, Hiroaki Kimura. 616-617 [doi]
- Equity of Learning Opportunities in the Chicago City of Learning ProgramDavid Quigley, Ogheneovo Dibie, Md. Arafat Sultan, Katie Van Horne, William R. Penuel, Tamara Sumner, Ugochi Acholonu, Nichole Pinkard. 618-619 [doi]
- Novel features for capturing cooccurrence behavior in dyadic collaborative problem solving tasksVikram Ramanarayanan, Saad Khan. 620-621 [doi]
- Adding eye-tracking AOI data to models of representation skills does not improve prediction accuracyMartina A. Rau, Zachary A. Pardos. 622-623 [doi]
- MATHia X: The Next Generation Cognitive TutorSteven Ritter, Stephen Fancsali. 624-625 [doi]
- Towards Integrating Human and Automated Tutoring SystemsSteven Ritter, Michael Yudelson, Stephen Fancsali, Susan R. Berman. 626-627 [doi]
- Toward Revision-Sensitive Feedback in Automated Writing EvaluationRod D. Roscoe, Matthew E. Jacovina, Laura K. Allen, Adam C. Johnson, Danielle S. McNamara. 628-629 [doi]
- Preliminary Results On Dialogue Act and Subact Classification in Chat-based Online Tutorial DialoguesVasile Rus, Rajendra Banjade, Nabin Maharjan, Donald M. Morrison, Steven Ritter, Michael Yudelson. 630-631 [doi]
- SAS Tools for Educational Data MiningJennifer Sabourin, Scott W. McQuiggan, André De Waal. 632-633 [doi]
- Applicability of Educational Data Mining in Afghanistan: Opportunities and ChallengesAbdul Rahman Sherzad. 634-635 [doi]
- Browsing-Pattern Mining from e-Book Logs with Non-negative Matrix FactorizationAtsushi Shimada, Fumiya Okubo, Hiroaki Ogata. 636-637 [doi]
- How employment constrains participation in MOOCs?Mina Shirvani Boroujeni, Lukasz Kidzinski, Pierre Dillenbourg. 638-639 [doi]
- Quantifying How Students Use an Online Learning System: A Focus on Transitions and PerformanceErica L. Snow, Andrew E. Krumm, Timothy E. Podkul, Mingyu Feng, Alex J. Bowers. 640-641 [doi]
- A Platform for Integrating and Analyzing Data to Evaluate the Impacts of Educational TechnologiesDaniel Stanhope, Karl Rectanus. 642-643 [doi]
- Educational Technology: What 49 Schools Discovered about Usage when the Data were UncoveredDaniel Stanhope, Karl Rectanus. 644-645 [doi]
- Learning curves versus problem difficulty: an analysis of the Knowledge Component picture for a given contextBrett van de Sande. 646-647 [doi]
- Validating Automated Triggers and Notifications @ Scale in Blackboard LearnJohn Whitmer, Aleksander Dietrichson, Bryan O'Haver. 648-649 [doi]
- Discovering 'Tough Love' Interventions Despite DropoutJoseph Jay Williams, Anthony Botelho, Adam Sales, Neil T. Heffernan, Charles Lang. 650-651 [doi]
- Stimulating collaborative activity in online social learning environments with Markov decision processesMatthew Yee-King, Mark d'Inverno. 652-653 [doi]
- Predicting student grades from online, collaborative social learning metrics using K-NNMatthew Yee-King, Andreu Grimalt-Reynes, Mark d'Inverno. 654-655 [doi]
- Meta-learning for predicting the best vote aggregation method: Case study in collaborative searching of LOsAlfredo Zapata Gonzalez, Víctor H. Menéndez, Cristóbal Romero, Manuel Emilio Prieto Méndez. 656-657 [doi]
- Soft Clustering of Physics Misconceptions Using a Mixed Membership ModelGuoguo Zheng, Seohyun Kim, Yanyan Tan, April Galyardt. 658-659 [doi]
- Perfect Scores Indicate Good Students !? The Case of One Hundred Percenters in a Math Learning SystemZhilin Zheng, Martin Stapel, Niels Pinkwart. 660-661 [doi]
- Towards the Understanding of Gestures and Vocalization Coordination in Teaching ContextRoghayeh Barmaki, Charles E. Hughes. 663-665 [doi]
- Towards Modeling Chunks in a Knowledge Tracing Framework for Students' Deep LearningYun Huang, Peter Brusilovsky. 666-668 [doi]
- Using Case-Based Reasoning to Automatically Generate High-Quality Feedback for Programming ExercisesAngelo Kyrilov. 669-671 [doi]
- Predicting Off-task Behaviors for Adaptive Vocabulary Learning SystemSungJin Nam. 672-674 [doi]
- Estimation of prerequisite skills model from large scale assessment data using semantic data miningBruno Elias Penteado. 675-677 [doi]
- Designing Interactive and Personalized Concept Mapping Learning EnvironmentsShang Wang. 678-680 [doi]
- Analysing and Refining Pilot TrainingBruno Emond, Scott Buffett, Cyril Goutte, Jaff Guo. 682-687 [doi]
- A Scalable Learning Analytics Platform for Automated Writing FeedbackJacqueline L. Feild, Nicholas Lewkow, Neil Zimmerman, Mark Riedesel, Alfred Essa. 688-693 [doi]
- An Automated Test of Motor Skills for Job Selection and FeedbackBhanu Pratap Singh Rawat, Varun Aggarwal. 694-699 [doi]
- Studying Assignment Size and Student Performance Using Propensity Score MatchingShirin Mojarad. 701-702 [doi]
- Toward Automated Support for Teacher-Facilitated Formative Feedback on Student WritingJennifer Sabourin, Lucy Kosturko, Kristin Hoffmann, Scott W. McQuiggan. 703-704 [doi]
- TutorSpace: Content-centric Platform for Enabling Blended Learning in Developing CountriesKuldeep Yadav, Kundan Shrivastava, Ranjeet Kumar, Saurabh Srivastava, Om Deshmukh. 705-706 [doi]